Putting It All Together

Linear regression using PyTorch complete steps

We have covered a lot of ground so far. From coding a linear regression in Numpy using gradient descent to transforming it into a PyTorch model, this is all done step-by-step.

It is time to put it all together and organize our code into three fundamental parts, namely:

• Data preparation (not data generation)

• Model configuration

• Model training

Let us tackle these three parts in order.

Data preparation

To be honest, there isn’t much data preparation at this point. After generating our data points in the data generation lesson, the only preparation step performed so far was transforming Numpy arrays into PyTorch tensors, which can be seen below: